Conventional positioning systems for mobile devices, such as dedicated navigation device and smart phones having navigation components, such as a global positioning systems (GPS) receiver, require continuous reception and processing of external signals to calculate device location. These systems can provide highly accurate geographic positioning, but consume large amounts of battery power. For example, though some mobile devices have standby times, or “on” times of about 100 hours or more, they can only operate about 2 to 4 hours with GPS running continuously. These positioning systems also depend on an ability to receive the positioning signals, and users can become lost or miss a turn when signal strength is weak.
Onboard systems for measuring movement of the mobile device, such as an inertial navigation unit (INU), use much less power and provide highly accurate displacement information for a period of time. Location of the mobile device can be determined based on a location fix, such as from a GPS unit and the measured movements. Use of movement-measuring systems, such as INUs, has increased in recent years due to their low power usage, increasing accuracy, and decreasing cost. INUs, though, suffer integration drift: slight errors accumulating with time. Eventually, the resulting location becomes unreliable. For this reason, INUs are typically used only as a backup to GPS in a mobile device for providing positioning information when the GPS is out of coverage (e.g., in a coverage shadow of a tunnel or building).
A positioning system intelligently leveraging the benefits of both movement-measuring and signal-dependent positioning subsystems would greatly improve the ability to accurately determine location of a mobile device for long periods of time. Such a system would also enhance the effectiveness of location-based services (LBSs).